Paper Citation Record · LEDGER

Maximum Likelihood for Logistic Regression Model with Incomplete and Hybrid-Type Covariates

As of 8 August 2026, this Paper Citation Record lists 32 of 32 outbound references and 0 inbound Pith citation observations for arXiv:2506.03445.

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pith.paper-citation-record.v1
2506.03445 v1

Coverage vector

measured 32 of 32 reference resolution

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Source: paper_references, paper_reference_links, observed 2026-08-07T11:08:28.106508Z

measured 32 of 32 standing notices

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Pith citing papers itemized under the disclosed page cap.

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Reference resolution

32 of 32 outbound references displayed

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External citation measurements

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Outbound references

Observation 8d0c96ee-348c-458b-8e0b-f6cd65392ded · outbound

This paper cites an unresolved cited work.

Maximum Likelihood for Logistic Regression Model with Incomplete and Hybrid-Type Covariates Unresolved cited work

Reference 1

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Observation ba989b0f-9b57-4bb5-a926-21579f34ec52 · outbound

This paper cites A logistic regress ion approach to ﬁeld estimation using binary measurements,.

Maximum Likelihood for Logistic Regression Model with Incomplete and Hybrid-Type Covariates A logistic regress ion approach to ﬁeld estimation using binary measurements,

Reference 2

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Observation 5ffb3444-3b5b-4db6-9f57-6687dea9eae0 · outbound

This paper cites Modiﬁed multi-directi on iterative algorithm for separable nonlinear models with missing data,.

Maximum Likelihood for Logistic Regression Model with Incomplete and Hybrid-Type Covariates Modiﬁed multi-directi on iterative algorithm for separable nonlinear models with missing data,

Reference 3

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Observation 9979dcce-4b77-4228-bbd9-a7821ca5c0fa · outbound

This paper cites What do we do with missing data? some o ptions for analysis of incomplete data,.

Maximum Likelihood for Logistic Regression Model with Incomplete and Hybrid-Type Covariates What do we do with missing data? some o ptions for analysis of incomplete data,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:08:34.716942Z

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This paper cites Robust subspace tracking with missing data and outliers: Novel algorithm with convergence guarantee,.

Maximum Likelihood for Logistic Regression Model with Incomplete and Hybrid-Type Covariates Robust subspace tracking with missing data and outliers: Novel algorithm with convergence guarantee,

Reference 5

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Observation 28a9c5a2-6c20-42e7-a298-65b427b65662 · outbound

This paper cites Missing data,.

Maximum Likelihood for Logistic Regression Model with Incomplete and Hybrid-Type Covariates Missing data,

Reference 6

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Observation f5b4d42a-29b0-4008-9622-09ea5b99afbc · outbound

This paper cites Robust low-rank covariance matrix September 16, 2025 DRAFT 11 estimation with a general pattern of missing values,.

Maximum Likelihood for Logistic Regression Model with Incomplete and Hybrid-Type Covariates Robust low-rank covariance matrix September 16, 2025 DRAFT 11 estimation with a general pattern of missing values,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:08:33.915193Z

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Observation 621045b6-76f1-4896-9dc7-99d24a6b93fa · outbound

This paper cites A principal compon ent method to impute missing values for mixed data,.

Maximum Likelihood for Logistic Regression Model with Incomplete and Hybrid-Type Covariates A principal compon ent method to impute missing values for mixed data,

Reference 8

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Observation f3d9652a-5e83-46c8-b1ac-5be27cf9d964 · outbound

This paper cites Multivariate correlation model s with mixed discrete and continuous variables,.

Maximum Likelihood for Logistic Regression Model with Incomplete and Hybrid-Type Covariates Multivariate correlation model s with mixed discrete and continuous variables,

Reference 9

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Observation a6f214af-3240-4356-b1eb-925c8b2d0803 · outbound

This paper cites Maximum likelihood e stimation for mixed continuous and categorical data with missing values,.

Maximum Likelihood for Logistic Regression Model with Incomplete and Hybrid-Type Covariates Maximum likelihood e stimation for mixed continuous and categorical data with missing values,

Reference 10

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Observation 66a25bc4-159b-457e-9e14-c9f09fababd0 · outbound

This paper cites Maximum lik elihood from incomplete data via the em algorithm,.

Maximum Likelihood for Logistic Regression Model with Incomplete and Hybrid-Type Covariates Maximum lik elihood from incomplete data via the em algorithm,

Reference 11

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Observation a5ab77c2-890b-4afa-92c7-3e5712080d36 · outbound

This paper cites Parameter e stimation of heavy-tailed ar model with missing data via stochastic EM,.

Maximum Likelihood for Logistic Regression Model with Incomplete and Hybrid-Type Covariates Parameter e stimation of heavy-tailed ar model with missing data via stochastic EM,

Reference 12

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Observation c61a5d64-a049-4205-b12b-b6bf5ca9fde9 · outbound

This paper cites Missforest—non-parametric missing value imputation for mixed- type data,.

Maximum Likelihood for Logistic Regression Model with Incomplete and Hybrid-Type Covariates Missforest—non-parametric missing value imputation for mixed- type data,

Reference 13

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Observation 92ce10ec-678c-4148-a487-cacdd6322c15 · outbound

This paper cites Logistic regression with missing responses and predictors: a review of existing approaches and a case study.

Maximum Likelihood for Logistic Regression Model with Incomplete and Hybrid-Type Covariates Logistic regression with missing responses and predictors: a review of existing approaches and a case study

Reference 14

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Observation 4dfe899f-b1b4-4bec-a3dc-ce7dfa5be06d · outbound

This paper cites On the application of generali zed linear mixed models for predicting path loss in lte networks,.

Maximum Likelihood for Logistic Regression Model with Incomplete and Hybrid-Type Covariates On the application of generali zed linear mixed models for predicting path loss in lte networks,

Reference 15

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Observation 135a9fbd-9251-4463-8ee2-98318b0ea5fd · outbound

This paper cites Logistic regression with missing covari- ates—parameter estimation, model selection and predictio n within a joint-modeling framework,.

Maximum Likelihood for Logistic Regression Model with Incomplete and Hybrid-Type Covariates Logistic regression with missing covari- ates—parameter estimation, model selection and predictio n within a joint-modeling framework,

Reference 16

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Observation c9dd151b-73ee-468f-8017-4ee3324757cb · outbound

This paper cites Robust inference with incompleteness for logistic regression model,.

Maximum Likelihood for Logistic Regression Model with Incomplete and Hybrid-Type Covariates Robust inference with incompleteness for logistic regression model,

Reference 17

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Observation a331b30c-dbbb-4b8e-815f-fc4ae971e3a3 · outbound

This paper cites High-dimensional logistic regression with missing data: Imputation, regularization, and universality.

Maximum Likelihood for Logistic Regression Model with Incomplete and Hybrid-Type Covariates High-dimensional logistic regression with missing data: Imputation, regularization, and universality

Reference 18

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Observation b0259198-e870-4708-b052-2d8ef4f85dbd · outbound

This paper cites Deeply lear ned generalized linear models with missing data,.

Maximum Likelihood for Logistic Regression Model with Incomplete and Hybrid-Type Covariates Deeply lear ned generalized linear models with missing data,

Reference 19

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Observation 6df4ecdb-9d8d-435d-a084-1fb8dadee3aa · outbound

This paper cites Improving penaliz ed logistic regression model with missing values in high-dimensional data,.

Maximum Likelihood for Logistic Regression Model with Incomplete and Hybrid-Type Covariates Improving penaliz ed logistic regression model with missing values in high-dimensional data,

Reference 20

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Observation 89ff5f4c-d274-45d1-b925-f9e6da70e9a0 · outbound

This paper cites Convergence o f a stochastic approximation version of the em algorithm,.

Maximum Likelihood for Logistic Regression Model with Incomplete and Hybrid-Type Covariates Convergence o f a stochastic approximation version of the em algorithm,

Reference 21

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Observation 8d58b712-44ae-4b1d-b921-f35e2e0f94c1 · outbound

This paper cites Student’s t var modeling with missing data via September 16, 2025 DRAFT 12 stochastic em and gibbs sampling,.

Maximum Likelihood for Logistic Regression Model with Incomplete and Hybrid-Type Covariates Student’s t var modeling with missing data via September 16, 2025 DRAFT 12 stochastic em and gibbs sampling,

Reference 22

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Observation aae6e6aa-027a-4218-8333-515883f6a03a · outbound

This paper cites Dynamic expectation-maximization algorithms for mixed-type data,.

Maximum Likelihood for Logistic Regression Model with Incomplete and Hybrid-Type Covariates Dynamic expectation-maximization algorithms for mixed-type data,

Reference 23

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Observation 84c2777c-7df2-4004-a698-cf96b54b6494 · outbound

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Maximum Likelihood for Logistic Regression Model with Incomplete and Hybrid-Type Covariates Missing co variates in generalized linear models when the missing data mechanism is non-ignorable,

Reference 24

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Observation a41d43bf-d23b-420e-9314-b6b545339f51 · outbound

This paper cites Coupling a stochastic approxi mation version of emwith an mcmc procedure,.

Maximum Likelihood for Logistic Regression Model with Incomplete and Hybrid-Type Covariates Coupling a stochastic approxi mation version of emwith an mcmc procedure,

Reference 25

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Observation b2f0659a-c60e-4740-9f7c-a15c47203a1c · outbound

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Maximum Likelihood for Logistic Regression Model with Incomplete and Hybrid-Type Covariates mice: Multi variate imputation by chained equations in r,

Reference 26

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Source-reported events for the cited work

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Observation 5fcaaad9-db96-4c4c-a5e8-3b6d0edb8580 · outbound

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Maximum Likelihood for Logistic Regression Model with Incomplete and Hybrid-Type Covariates Missing data imputation: focusing on single imputation,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:08:29.684999Z

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Observation 843ade25-93f5-4696-ad02-b2ad62e60c60 · outbound

This paper cites Saem al gorithm for mixed data imputation (binary/categorical/continuous),.

Maximum Likelihood for Logistic Regression Model with Incomplete and Hybrid-Type Covariates Saem al gorithm for mixed data imputation (binary/categorical/continuous),

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:08:29.489019Z

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Observation 93c5ccfb-8a49-44d5-b7fe-ed26d91164cc · outbound

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Maximum Likelihood for Logistic Regression Model with Incomplete and Hybrid-Type Covariates Heart Disease,

Reference 29

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Observation e8532bd2-29b6-4cf5-bd47-ba0a97acb18f · outbound

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Maximum Likelihood for Logistic Regression Model with Incomplete and Hybrid-Type Covariates Algerian Forest Fires,

Reference 30

Resolution: verified exact; doi, observed 2026-08-07T11:08:28.360885Z

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Observation 63e6b887-3777-4f5c-b8eb-56571e0006f6 · outbound

This paper cites Titanic: Machine learning from dis aster,.

Maximum Likelihood for Logistic Regression Model with Incomplete and Hybrid-Type Covariates Titanic: Machine learning from dis aster,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:08:29.296145Z

Source-reported events for the cited work

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Observation ac247696-38b4-4440-8f4e-16c63a9d60b4 · outbound

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Maximum Likelihood for Logistic Regression Model with Incomplete and Hybrid-Type Covariates The 1974 motor trend car r oad tests,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:08:29.104213Z

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